Abnormal heart rhythms can be indicative of serious health problems and, as such, it is important to accurately identify them as soon as possible so that an appropriate plan of treatment or management may be implemented. It is currently difficult to accurately diagnose and quantitatively evaluate cardiac arrhythmias such as tachycardia and a “missed beat”. Conventional techniques relying on ECG data are not effective for certain use cases, such as when examining a fetal heart, due to a relatively weak signal-to-noise ratio. Additionally, ECG data provides information about electrical signals traveling across the patient's heart and electrical signals are not always perfectly correlated with mechanical or hemodynamic motions of the heart. As such, it is desirable to understand the mechanical or hemodynamic motions of the patient's heart.
Ideally, the clinician would be provided with an accurate representation of a heart's mechanical or hemodynamic motions. Convention techniques relying on ultrasound data often involve a clinician viewing a cine loop based on ultrasound data and attempting to visually identify a cardiac arrhythmia. There are several problems with the conventional manual approach including high inter-operator variability, low repeatability, and an overly large dependence on the skill and experience of the operator.
For these and other reasons an improved ultrasound imaging system and method of obtaining, displaying and analyzing data regarding cardiac periodicity is desired.